A non-transitory recording medium storing a computer readable influence calculation program causes a computer to perform: acquiring a first communication history between a first person and a second person; acquiring a second communication history between the second person and a third person; and calculating an influence score of the first person on a plurality of persons including the second person and the third person, in accordance with information including the first communication history and the second communication history.
1. A non-transitory recording medium storing a computer readable influence calculation program for causing a computer to perform: acquiring a first communication history between a first person and a second person; acquiring a second communication history between the second person and a third person; and calculating an influence score of the first person on a plurality of persons including the second person and the third person, in accordance with information including the first communication history and the second communication history.
2. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes the number of the second persons and the number of the third persons.
3. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes a value obtained by multiplying the number of the second persons by a first coefficient, and a value obtained by multiplying the number of the third persons by a second coefficient, the second coefficient being smaller than the first coefficient.
4. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes a sum of influence scores of the second person on the plurality of persons.
5. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes betweenness centrality of the first person.
6. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes the number of times communication has been performed between the first person and the second person, and the number of times communication has been performed between the second person and the third person.
7. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes the number of times transmission from the first person to the second person has been performed, and the number of times transmission from the second person to the third person has been performed.
8. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes the number of times reception from the second person has been performed by the first person, and the number of times reception from the third person has been performed by the second person.
9. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes the number of destinations from the first person to the second person, and the number of destinations from the second person to the third person.
10. The non-transitory recording medium storing a computer readable influence calculation program according to claim 1, wherein the information includes the number of types of destinations from the first person to the second person, and the number of types of destinations from the second person to the third person.
11. An influence calculation device comprising: a hardware processor that: acquires a first communication history between a first person and a second person; acquires a second communication history between the second person and a third person; and calculates an influence score of the first person on a plurality of persons including the second person and the third person, in accordance with information including the first communication history and the second communication history.
 Japanese Patent Application No. 2016-177401 filed on Sep. 12, 2016, including description, claims, drawings, and abstract the entire disclosure is incorporated herein by reference in its entirety.
 The present disclosure relates to an influence calculation program and an influence calculation device.
 Normally, how information spreads across an entire organization varies depending on which one of the persons belonging to the organization the information is transmitted to. In a case where a person wishes to transmit information across the organization, for example, if the respective roles of the persons belonging to the organization are apparent, it is possible to recognize to which one of the persons the information should be transmitted so as to appropriately transmit the information across the organization. JP 2006-155421 A discloses a method of estimating the characteristics of the subject person among the persons, using the e-mail communication history of the subject person. According to JP 2006-155421 A, the characteristics indicate that the subject person is a leader, or the subject person is a loner, for example. A person can recognize that it is possible to appropriately transmit information across the organization by transmitting the information to a person having the characteristics of a leader.
 According to the invention disclosed in JP 2006-155421 A, however, only the communication history between the subject person and a person who has communicated with the subject person is used, and therefore, the influence score of the subject person on other persons cannot be accurately calculated, with the characteristics of the subject person being an example.
 The present disclosure has been made in view of such circumstances, and an object thereof is to provide an influence calculation program and an influence calculation device.
 To achieve the abovementioned object, according to an aspect of the present invention, a non-transitory recording medium storing a computer readable influence calculation program reflecting one aspect of the present invention causes a computer to perform: acquiring a first communication history between a first person and a second person; acquiring a second communication history between the second person and a third person; and calculating an influence score of the first person on a plurality of persons including the second person and the third person, in accordance with information including the first communication history and the second communication history.
 FIG. 29 is a diagram showing an example of the influence score display screen of the display device of another embodiment.
 Hereinafter, one or more embodiments of the present invention will be described with reference to the drawings. However, the scope of the invention is not limited to the disclosed embodiments. In the description below, like components and constituent elements are denoted by like reference numerals. Like components and constituent elements also have like names and functions. Therefore, explanation of them will not be repeated.
 FIG. 1 is a diagram for explaining an example configuration of an influence calculation system 20 according to this embodiment. The influence calculation system 20 includes a mail server 2, a collection device 4, a database (DB) 6, an influence calculation device 8, and a display device 10.
 The mail server 2 is connected to another mail server (not specifically shown). The mail server 2 transmits/receives electronic mail to/from this mail server. The collection device 4 collects mail information from the mail server 2 on a regular basis (every month, for example), and stores the mail information into the DB 6. Here, the mail information includes transmission dates, sources, destinations, titles, and message bodies of electronic mail, as shown in FIG. 4. The DB 6 stores various kinds of information, as well as the mail information.
 The influence calculation device 8 calculates the influence score of a subject person on other persons. The display device 10 displays the calculated influence score. The display device 10 may be a device such as a personal computer (PC), a smartphone, or a tablet. In this embodiment, the influence calculation device 8 and the display device 10 are formed with different housings from each other. In a modification, the influence calculation device 8 and the display device 10 may be integrally formed.
 FIG. 2 is a diagram showing the hardware configuration of the influence calculation device 8. As shown in FIG. 2, the influence calculation device 8 includes a central processing unit (CPU) 81 that executes programs, a read only memory (ROM) 82 that stores data in a nonvolatile manner, a random access memory (RAM) 83 that stores data in a volatile manner, a flash memory 84, operation keys 87 that accept instruction inputs from the user of the influence calculation device 8 (the user being the manager of the influence calculation system 20, for example), and a communication interface (IF) 88.
 The flash memory 84 is a nonvolatile semiconductor memory. The flash memory 84 stores the operating system and various kinds of programs to be executed by the CPU 81, and various kinds of content and data. The flash memory 84 also stores various kinds of data, such as data generated by the influence calculation device 8 and data obtained from a device outside the influence calculation device 8, in a volatile manner.
 FIG. 3 is a diagram showing the hardware configuration of the display device 10. As shown in FIG. 3, the display device 10 includes a CPU 101 that executes programs, a ROM 102 that stores data in a nonvolatile manner, a RAM 103 that stores data in a volatile manner, a flash memory 104, a display 105, operation keys 107 that accept instruction inputs from the user of the display device 10, and a communication interface (IF) 108.
 The display 105 displays various kinds of information in accordance with instruction inputs from the user of the display device 10. The flash memory 104 is a nonvolatile semiconductor memory. The flash memory 104 stores the operating system and various kinds of programs to be executed by the CPU 101, and various kinds of content and data. The flash memory 104 also stores various kinds of data, such as data generated by the display device 10 and data obtained from a device outside the display device 10, in a volatile manner.
 FIG. 4 shows an example of a mail DB that is a DB included in the DB 6 and stores mail information. In the example shown in FIG. 4, a mail information ID is assigned to each set of mail information. As for the mail information with a mail ID "1" in the example shown in FIG. 4, the mail transmission date is 10 o'clock on Apr. 2, 2016, the source is a person A, and the destination is a person B. In FIG. 4, "xxxx" is shown as the title and the message body. In reality, however, the text of the title and the text of the message body of the e-mail transmitted from the person A to the person B are stored in the mail DB. In the example shown in FIG. 4, persons are written as the sources and the destinations, but the transmitters that transmit e-mail and the receivers that receive e-mail are terminals owned by the persons. As for the mail information with the mail ID "1", for example, the source is a terminal owned by the person A, and the destination is a terminal owned by the person B.
 The influence calculation device 8 of this embodiment calculates respective influence scores of the six persons, or the persons A through F, which are shown as the sources and the destinations in FIG. 4. Next, influence scores are described. The influence calculation device 8 of this embodiment calculates the influence score of a subject person on the other persons (or the other five persons) among the six persons. In a case where the subject person is A, for example, the influence calculation device 8 calculates the influence score of the person A on the persons B through F. In this embodiment, the persons A through F belong to a predetermined group. A group is a concept such as a company, an organization, or a department.
 An influence score may be a value that indicates how well information can be transmitted to all the persons belonging to the group when communication with a person is made (or the information is transmitted to the person). In view of this, an influence score is also called a communication value. Also, an influence score may be a value that indicates how much all the persons belonging to the group are influenced when communication with a person is made (or information is transmitted to the person). Here, the information to be transmitted may be information to be transmitted via electronic mail, information to be transmitted orally, or information to be transmitted in writing. Also, an influence score may be a value that indicates how much all the persons belonging to the group can be influenced.
 In the example case described below, a person M who does not know the persons A through F wishes to transmit information to all the persons belonging to the group. If the person M recognizes the respective influence scores of the persons A through F in this case, the person M can realize that it is possible to transmit information smoothly to each of the persons A through F by transmitting the information to the person with the highest influence score. Also, in a case where the person M wishes to consult about his/her worries or the like, the person M can realize that the possibility of solving his/her worries is higher when the person M consults the person with the highest influence score than when the person M consults some other person among the persons A through F. As described above, even in a case where the person M does not know the persons A through F, the person M can recognize the respective influence scores of the persons A through F, so that the convenience in transmitting information to the persons A through F can be increased, for example.
 FIG. 5 is a functional block diagram for explaining the functional configuration of the influence calculation device 8. As shown in FIG. 5, the influence calculation device 8 includes an acquiring unit 816, a relationship extracting unit 811, and a calculating unit 824. The acquiring unit 816 includes a first acquiring unit 818 and a second acquiring unit 820. The relationship extracting unit 811 includes a relationship list generating unit 812 and an adjacency matrix generating unit 814.
 The relationship extracting unit 811, the acquiring unit 816, and the calculating unit 824 are formed through arithmetic processing performed by the CPU 81.
 The relationship list generating unit 812 acquires mail information equivalent to a predetermined period T (three months, for example) from the DB 6. Here, the mail information acquired by the relationship list generating unit 812 in the predetermined period T is the mail information shown in FIG. 4. In the description below, in a case where a person 0 and a person P have communicated with each other in the past predetermined period T, "the person 0 and the person P have a relationship". Here, communicating includes both transmitting information and receiving information. Meanwhile, the information includes e-mail and messages. In a case where the person 0 and the person P have not communicated with each other through e-mail in the past predetermined period T, on the other hand, "the person 0 and the person P do not have any relationship".
 The relationship list generating unit 812 generates a relationship list by determining whether there is a relationship with each person from the acquired mail information. From the mail information, the relationship list generating unit 812 extracts the relationships with the persons with whom e-mail has been exchanged, for example. The relationship list generating unit 812 determines that "a person who has transmitted e-mail and a person who has received the transmitted e-mail" are "persons who have exchanged e-mail". In this manner, the relationship list generating unit 812 sets a pair of the persons who have exchanged the e-mail. If there are more than one destination from the source, the relationship with the destinations are extracted.
 In the description below, e-mail transmission from the person A to the person B is shown as "A.fwdarw.B". As for the mail ID "3" in FIG. 4, for example, the relationship list generating unit 812 determines that there are the two kinds of relationships, "C.fwdarw.D" and "C.fwdarw.B". The relationship list generating unit 812 of this embodiment does not take into consideration which one of the persons who have exchanged e-mail is the source or the destination. Specifically, in FIG. 4, there are the relationship "B.fwdarw.C" and the relationship "C.fwdarw.B". However, the relationship list generating unit 812 regards these relationships as identical, and determines that there is a relationship between B and C.
 FIG. 6 shows an example of a relationship list generated by the relationship list generating unit 812. By the above described determination method, the relationship list generating unit 812 generates the relationship list shown in FIG. 6 from the mail information shown in FIG. 4. As can be seen from the example shown in FIG. 6, there are relationships between the person A and the person B, the person B and the person C, the person C and the person D, the person C and the person E, and the person C and the person F. The relationship list generating unit 812 transmits the generated relationship list to the adjacency matrix generating unit 814.
 The adjacency matrix generating unit 814 generates an adjacency matrix Z in accordance with the relationship list. The adjacency matrix Z is a matrix indicating the relationships between the persons who have communicated with each other through e-mail (exchanged e-mail with each other) in the predetermined period T. The row and column sizes of the adjacency matrix Z are determined by the number of persons whose influence scores are to be calculated. In a case where the number of persons whose influence scores are to be calculated is N (N being a natural number), the adjacency matrix Z is an N-by-N matrix. Since the number of persons whose influence scores are to be calculated is six (the persons A through F), a 6-by-6 matrix is generated as the adjacency matrix Z. The adjacency matrix Z is shown below.
 FIG. 7 shows the adjacency matrix Z in the form of a table. In the example shown in FIG. 7, the persons A through F are assigned to the respective rows and the respective columns. In the example shown in FIG. 7, "1" at each portion where a person shown as a column component and a person shown as a row component cross each other indicates that these persons have communicated with each other through e-mail in the predetermined period T (or have a relationship). On the other hand, "0" at each portion where a person shown as a column component and a person shown as a row component cross each other indicates that these persons have not communicated with each other through e-mail in the predetermined period T (or have no relationship).
 For example, since the portion where the person A and the person B cross each other shows "1", there is a relationship between the person A and the person B (also see FIG. 6). Meanwhile, since the portion where the person A and the person C cross each other shows "0", there is no relationship between the person A and the person C (also see FIG. 6). In FIG. 7 and the adjacency matrix Z, the portion where the person A in the row direction and the person A in the column direction cross each other is the origin, each component in the x-axis direction is an x-component, and each component in the y-axis direction is a y-component. For example, in FIG. 7, (3, 4) as a component (x, y) is "1", which indicates that there is a relationship between the person C and the person D. The adjacency matrix Z generated by the adjacency matrix generating unit 814 is input to the calculating unit 824.
 The calculating unit 824 calculates the influence score of each of the persons A through F in accordance with the adjacency matrix Z. FIG. 8 is a diagram showing the contents of the adjacency matrix Z. In FIG. 8, each circle represents a person (a node), and each line indicates a relationship. For example, the person A has a relationship with the person B, but has no relationship with each of the persons C through F. Also, the person C has a relationship with the person B and a relationship with each of the persons D through F, but has no relationship with the person A. Hereinafter, the subject person whose influence score is to be calculated will be referred to as a "first person". A person who has communicated with the first person within the predetermined period T will be referred to as a "second person". A person who has communicated with the second person within the predetermined period T will be referred to as a "third person". A person who has communicated with a certain person within the predetermined period T will be referred to as a communication person. Further, a diagram showing exchanges of e-mail as shown in FIG. 8 will also be referred to as a network.
 Where the calculating unit 824 calculates influence scores, a concept of "generation" is used. A generation indicates closeness to the first person. From the viewpoint of the first person, the generation of the first person is "0". From the viewpoint of the first person, the generation of a second person is "1". From the viewpoint of the first person, the generation of a third person is "2". In a case where the first person is the person B, for example, the person A and the person C are second persons, and the person D, the person E, and the person F are third persons.
 FIG. 9 shows the generations in a case where "the first person whose influence score is to be calculated by the calculating unit 824" is the "person B". In this case, the generation G of the person B is "0", the generation G of each of the persons A and C is "1", and the generation G of each of the persons D through F is "2". Each person of the generation "1" is also called a first-generation person, and each person of the generation "2" is also called a second-generation person.
 Next, the set of N (six in this embodiment) persons specified in the relationship list is defined as shown below.
N is a natural number. In this embodiment, X.sub.1 represents the person A, X.sub.2 the person B, X.sub.3 the person C, X.sub.4 the person D, X.sub.5 the person E, and X.sub.6 the person F. Using Equation 1 shown below, the calculating unit 824 calculates the influence score of a person X,. Here, 1.ltoreq.i.ltoreq.N, and i represents a natural number.
 Next, Equation 1 is described. The set of the jth-generation persons counted from the first person (the subject person) X.sub.i is defined as shown below. Here, j is a natural number. The number of jth-generation persons is M (M being a natural number).
 Z.sub.kn represents an element having k as the x-component and n as the y-component in the adjacency matrix Z. Here, k is expressed as: k=index(X.sub.m.sup.(i, j))). Meanwhile, index( ) represents a function that returns the index in the relationship list. In the following, index(X.sub.m.sup.(i, j)) is further described. In the relationship list, indexes "1" through "6" are assigned to the persons A through F, respectively. Here, index(X.sub.m.sup.(i, j)) returns the index associated with X.sub.m.sup.(i, j). In a case where X.sub.m.sup.(i, j) is the person E, for example, index(X.sub.m.sup.(i, j)) returns "5" as the index.
 Meanwhile, .alpha..sup.(j) is the coefficient by which a jth generation calculation result is to be multiplied. The coefficient .alpha. is set beforehand so as to become smaller as the value of a generation G becomes greater. For example, the coefficient .alpha. is the reciprocal of the value of a generation G. For example, the coefficient .alpha. for a person of the generation "1" is "1", and the coefficient .alpha. for a person of the generation "2" is "0.5". FIG. 10 shows the coefficients of persons of the respective generations. The manager of the influence calculation device 8, for example, determines up to which generation counted from the first person should be reflected in calculating influence scores. In this embodiment, the persons up to the second generation counted from the first person are reflected.
 Also, a value D(X.sub.i) may be used in calculating C(X.sub.i), which is the influence score of the person X.sub.i, according to Equation 1. D.sub.j(X.sub.i) represents the total number of persons of the first through jth generations counted from the person X.sub.i. Consequently, the influence score of a person X.sub.j can also be expressed by Equation 2 shown below. D.sub.j(X.sub.i) is generated from the relationship list or the adjacency matrix Z.
 In a case where the first person whose influence score is to be calculated is the person B, j is 2, .alpha..sup.(1) is 1, and .alpha..sup.(2) is 0.5, for example, the influence score C(B) of the person B is calculated as shown below.
 It should be noted that the number of persons of the first generation is the number of second persons. Meanwhile, the number of persons of the second generation is the number of third persons. In Equation 3, "the number of persons of the first generation counted from the person B" is determined from a first communication history. The first communication history is a history of communication between the first person and a second person. The first acquiring unit 818 also acquires the first communication history. Meanwhile, "the number of persons of the second generation counted from the person B" is determined from a second communication history. The second communication history is a history of communication between the second person and a third person. The second acquiring unit 820 acquires the second communication history. In this manner, the first communication history and the second communication history are used in Equation 1 and Equation 2. That is, the calculating unit 824 calculates the influence scores of the respective persons, using the first communication history acquired by the first acquiring unit 818 and the second communication history acquired by the second acquiring unit 820.
 FIG. 11 is a diagram showing the influence scores of the respective persons calculated by the calculating unit 824. In FIG. 11, an influence score is shown in the vicinity of each person. For example, the influence score of the person A is "2", and the influence score of the person B is "4.5".
 After the calculating unit 824 calculates the influence scores of all the persons specified in the relationship list, the influence scores of all the persons are transmitted to the DB 6 via the communication IF 88 (see FIG. 2). The DB 6 stores the transmitted influence scores of all the persons as an influence score DB.
 FIG. 12 is a table showing an example of the influence score DB. In the example shown in FIG. 12, domain names and the influence scores calculated for the respective persons by the calculating unit 824 are stored in the influence score DB. The domain names are specified by mail addresses assigned to the respective persons. As for the person A, "ppp.local" is stored as the domain, and "1.5" is stored as the influence score, for example. In this embodiment, a group name can be identified from a domain. For example, the group to which the persons having mail addresses with the domain "ppp.local" is group P. The group to which the persons having mail addresses with a domain "qqq.local" is group Q.
 FIG. 13 shows a flowchart of a process to be performed by the influence calculation device 8. Referring now to FIG. 13, the flowchart of a process to be performed by the influence calculation device 8 is described. In S2, the relationship list generating unit 812 acquires mail information. In S4, in accordance with the acquired mail information, the relationship list generating unit 812 generates a relationship list (see FIG. 6). In S6, in accordance with the generated relationship list, the adjacency matrix generating unit 814 generates the adjacency matrix Z. In S8, in accordance with the relationship list and Equation 1, the calculating unit 824 calculates the influence scores of all the persons (the persons A through F) specified in the relationship list. As the influence calculation device 8 transmits the calculated influence scores of all the persons specified in the relationship list to the DB 6, the influence scores of all the persons are stored into the influence score DB in the DB 6.
 FIG. 14 shows a flowchart of the relationship list generation process (S4 in FIG. 13) to be performed by the relationship list generating unit 812. In S42, before generating the relationship list, the relationship list generating unit 812 determines whether there remains unprocessed mail information in the mail information that is equivalent to the predetermined period T and has been transmitted from the collection device 4. If the relationship list generating unit 812 determines that there remains unprocessed mail information (YES in S42), the process moves on to S44.
 In S44, the relationship list generating unit 812 acquires the next mail information from the remaining unprocessed mail information in the mail information that is equivalent to the predetermined period T and has been transmitted from the collection device 4. In S46, the source and the destination indicated by the mail information acquired in S44 are paired with each other. As for the persons who have already been paired at the time of S46, no processing needs to be performed for them, and the processing in S46 is ended. If the relationship list generating unit 812 determines in S42, before generating the relationship list, that there remains no unprocessed mail information in the mail information that is equivalent to the predetermined period T and has been transmitted from the collection device 4 (NO in S42), the relationship list generating unit 812 ends the relationship list generation process.
 In the above manner, the influence calculation device 8 of this embodiment calculates the influence score of a person (a first person), using not only the first communication history between the first person and a second person who has communicated with the first person within the predetermined period T, but also the second communication history between the second person and a third person. Thus, the influence calculation device 8 of this embodiment can calculate influence scores more accurately than in a conventional case where the second communication history is not used while the first communication history is used.
 The display device 10 displays the influence score of each person, in accordance with information input from a user. Referring now to FIGS. 15 and 16, a process to be performed by the display device 10 is described. FIG. 15 shows an example of the input screen displayed by the display device 10. FIG. 16 shows an example of the influence score display screen displayed by the display device 10.
 When the input screen shown in FIG. 15 is displayed, a user can input a group name. For example, a cursor (not shown) is moved onto an input region 202 on the input screen shown in FIG. 15, and a group name is then input. In this embodiment, a domain name corresponding to a group name can be input to the input region 202. When the cursor is moved onto the input region 202, a tab showing all the domain names is displayed, for example. As the user selects a domain name from among the domain names displayed in the tab, the selected domain name is input to the input region 202. When a search button 204 is clicked with the domain name having been input to the input region 202, the influence score display screen shown in FIG. 16 is displayed.
 In the example case shown in FIG. 16, "ppp.com" is input as the domain name. In the example shown in FIG. 16, "persons with high influence scores at ppp.com" are displayed. As can be seen from the example shown in FIG. 16, in the group P, the person B has the highest influence score, and the person A has the second highest influence score. In the example shown in FIG. 16, mail addresses of the persons are also displayed along with the names of the persons.
 FIG. 17 shows a flowchart of a process to be performed by the CPU 101 of the display device 10. In S62, the CPU 101 determines whether a group name (a domain name) has been input thereto by a user. While the input screen shown in FIG. 15 is displayed, the CPU 101 stands by until a group name is input by a user (NO in S62). If the CPU 101 determines that a group name has been input thereto by a user (YES in S62), the process moves on to S64. In S64, a predetermined number of influence scores of the persons belonging to the domain designated by the user are acquired from the DB 6 (or the influence score DB shown in FIG. 12). In this embodiment, the predetermined number is three. When the processing in S64 is completed, the process moves on to S66. In S66, the persons with high influence scores are displayed on the display 105 in accordance with the acquired influence scores, as shown in FIG. 16. As for the persons with high influence scores, the name of the person with the highest influence score is displayed at the top, and the names of the other persons are displayed at the positions corresponding to their influence scores.
 With this configuration, a user can be made to recognize the persons with high influence scores in a group the user has input.
 Next, a second embodiment is described. The first embodiment has been described on the assumption that the influence scores of a person on the other persons are the same. For example, there may be two persons (a person X1 and a person X2) as persons having a relationship with a person X. In this case, the person X1 of the two persons may have a relationship with a large number of persons while the other person X2 has a relationship with a small number of persons. In this case, the person X1 and the person X2 should not be evaluated equally in terms of influence scores.
 For example, the person X1 having a relationship with a large number of persons is influential on the persons specified in the relationship list. Therefore, the relationship between the person X and the person X1 has a higher possibility of increasing the influence of the person X in the network than the relationship between the person X and the person X2. The centricity index that reflects the persons having relationships with the persons X1 and X2 having relationships with the person X in calculating the influence score of the person X as above may be eigenvector centricity. In this embodiment, the influence score of each person is calculated with eigenvector centricity. Using eigenvector centricity is using the sum of the influence scores of the second persons (the persons who have communicated with the first person within the predetermined period T).
 FIG. 18 is a flowchart of a process to be performed by the calculating unit 824 of the second embodiment. In S102, the calculating unit 824 sets the influence scores of all the persons (the persons A through F) specified in the relationship list to the initial values. Here, the initial value may be any value. In this embodiment, the initial value is "1".
 In S104, the calculating unit 824 updates the influence scores of all the persons A through F. In this embodiment, the calculating unit 824 updates the influence scores C1 of the persons A through F, using Equation 21 shown below.
 The set of N (six in this embodiment) persons specified in the relationship list is X=(X1, X2, X3, . . . , X.sub.i, . . . , X.sub.N). Here, 1.ltoreq.i.ltoreq.N. For example, X.sub.1 represents the person A, X.sub.2 the person B, X.sub.3 the person C, X.sub.4 the person D, X.sub.5 the person E, and X.sub.6 the person F. Meanwhile, 1.ltoreq.j.ltoreq.N, and i.noteq.j. In a modification, i may be equal to j (i=j). C1(X.sub.i) represents the influence score of a person i, and C1(X.sub.j) represents the influence score of a person j. In a case where i=2, for example, the influence score C1(X.sub.2) is the influence score of the person X.sub.2 or the person B. Z.sub.ij is the element shown at the portion where the ith person and the jth person cross each other in the adjacency matrix Z shown in FIG. 7. For example, Z.sub.34 is "1".
 When the processing in S104 is completed, the process moves on to S106. In S106, the calculating unit 824 divides the influence score updated in S104 by the maximum influence score. Here, the maximum influence score is the maximum value of the influence scores of all the persons updated in S104. In S108, a check is made to determine whether the influence scores of all the persons have converged. In S108 in this embodiment, if the residual sum of squares of the influence score before the update in S104 and the influence score after the update in S104 is determined to be smaller than a prescribed value, the influence scores of all the persons are determined to have converged. The residual sum of squares is expressed by Equation 22 shown below, for example.
 Here, C1(X.sub.i)' represents the influence score of a person X, before the update in S104, and C1(X.sub.i) represents the influence score of the person X, after the update in S104.
 According to this embodiment, the influence score of the first person can be calculated, with the influence scores of the second persons being taken into account. Thus, the influence score of the first person can be more accurately calculated.
 In this embodiment, eigenvector centricity is applied as shown in FIG. 18 and Equation 22. However, some other method may be used, as long as eigenvector centricity can be applied.
 Next, a third embodiment is described. In the third embodiment, the influence score of a first person is calculated with the use of the betweenness centrality of the first person. Here, betweenness centrality is a value that indicates how well the person is functioning as a contact or a hub in the network. The calculating unit 824 calculates the betweenness centrality B(X.sub.i) of the person X.sub.i, using Equation 31 shown below.
 In Equation 31, 1.ltoreq.r.ltoreq.N, and 1.ltoreq.s.ltoreq.N. In the network, .sigma..sub.rs represents the total number of the shortest paths between a person r and a person s, and .sigma..sub.rs(X.sub.i) represents the total number of the shortest paths between the person r and the person s among the paths extending through the person X.sub.i.
 FIG. 19 is a diagram for explaining the concept of betweenness centrality. In the example shown in FIG. 19, the network is different from the network shown in FIG. 8, and persons A through G are shown. In FIG. 19, a larger circle indicates a higher degree of betweenness centrality. Specifically, in FIG. 19, the person C, the person D, and the person E have a high degree of betweenness centrality, and the person A, the person B, the person F, and the person G have a low degree of betweenness centrality. In the example shown in FIG. 19, the person C, the person D, and the person E form an information transmission/reception path (a contact or a hub) in the network, and have a high degree of betweenness centrality.
 The calculating unit 824 calculates the betweenness centrality of each of the persons A through G, using Equation 31. The calculating unit 824 calculates the influence score of each person, using the calculated betweenness centrality. For example, an equation formed by substituting D.sub.j(X.sub.i) in Equation 2 described in the first embodiment with B(X.sub.i) calculated by Equation 31 may be used in calculating an influence score. Alternatively, the calculating unit 824 may calculate an influence score by setting the initial value described in S102 in FIG. 18 of the second embodiment as B(X.sub.i) calculated by Equation 31. Therefore, in the third embodiment, the first communication history and the second communication history include the betweenness centrality (or the value of the betweenness centrality) of each person.
 As described above, the calculating unit 824 of the third embodiment calculates the influence score of each person in accordance with betweenness centrality and the like. Thus, in the third embodiment, the influence score of each person can be calculated, with the betweenness centrality of the person being taken into account.
 In the adjacency matrix Z of the first embodiment, "1" is set, regardless of whether the number of times communication has been performed between persons is one. In a fourth embodiment, on the other hand, the calculating unit 824 calculates influence scores, using an adjacency matrix Z1 that reflects the number of times communication has been performed.
 FIG. 20 shows communication histories of persons A through D. In FIG. 20, the person A has transmitted e-mail to the person B under "To", and transmitted the e-mail to the person C under "CC (Carbon Copy)". In the example shown in FIG. 20, the number of times communication has been performed between the person A and the person B is two. The number of times communication has been performed between the person A and the person C is one. The number of times communication has been performed between the person A and the person D is two.
 The mail information acquired by the relationship list generating unit 812 in the predetermined period T is the mail information shown in FIG. 20. In accordance with the mail information, the relationship list generating unit 812 generates a relationship list. FIG. 21 is a table showing an example of the relationship list. The example in FIG. 21 shows that the number of times communication has been performed between the person A and the person B is two, the number of times communication has been performed between the person A and the person C is one, and the number of times communication has been performed between the person A and the person D is two.
 In accordance with the generated relationship list, the adjacency matrix generating unit 814 generates the adjacency matrix Z1. FIG. 22 shows the adjacency matrix Z1 in the form of a table. The adjacency matrix Z1 generated by the adjacency matrix generating unit 814 is input to the calculating unit 824. The calculating unit 824 calculates influence scores in accordance with the adjacency matrix Z1. For example, the calculating unit 824 calculates influence scores, using an equation formed by substituting Z.sub.kn in Equation 1 with Z1.sub.kn. In the fourth embodiment, the first communication history includes the number of times communication has been performed between a first person and a second person. The second communication history includes the number of times communication has been performed between the second person and a third person. Alternatively, the first communication history and the second communication history may include the number of times communication has been performed between the first person and a second person, and the number of times communication has been performed between the second person and a third person.
 According to the fourth embodiment, the calculating unit 824 can calculate influence scores that reflect the numbers of times communication has been performed. Thus, in the fourth embodiment, the influence score of each person can be calculated, with the number of times the person has performed communication being taken into account.
 In the first embodiment, the influence scores of the respective persons are calculated, with the numbers of destinations of transmission the respective persons have performed not being taken into account. When e-mail has been transmitted to a large number of destinations, the relationship between the transmitter of the e-mail and a recipient of the e-mail is normally weaker than that in a case where e-mail has been transmitted to only one destination. In view of this, influence scores are calculated in this embodiment, with the number of transmission destinations being taken into account.
 In this embodiment, the mail information acquired by the relationship list generating unit 812 in the predetermined period T is the mail information shown in FIG. 20. In accordance with the relationship list supplied from the relationship list generating unit 812, the adjacency matrix generating unit 814 generates an adjacency matrix. The relationship list of this embodiment is shown in FIG. 21. In a case where there is e-mail transmitted to two or more destinations, the adjacency matrix generating unit 814 multiplies the elements corresponding to the transmission by a coefficient. Here, the coefficient is such a coefficient that becomes smaller as the number of destinations to which the e-mail has been transmitted becomes larger. In this embodiment, the coefficient is the reciprocal of the number of destinations. It should be noted that some other method may be used in determining the coefficient. In the example shown in FIG. 21, the person A has transmitted e-mail to the person B and the person C. Therefore, the transmission of the e-mail from the person A to the person B, and the transmission of the d-mail from the person A to the person C are set as 1/2.
 FIG. 23 shows an adjacency matrix Z2 to be used in the fifth embodiment in the form of a table. The calculating unit 824 calculates influence scores in accordance with the adjacency matrix Z2. For example, the calculating unit 824 calculates influence scores, using an equation formed by substituting Z.sub.kn in Equation 1 with Z2.sub.kn. In the fifth embodiment, the first communication history includes the number of second persons as destinations to which the first person has transmitted e-mail. The second communication history includes the number of third persons as destinations to which a second person has transmitted e-mail. Alternatively, the first communication history and the second communication history may include the number of second persons as destinations to which the first person has transmitted e-mail, and the number of third persons as destinations to which a second person has transmitted e-mail.
 According to the fifth embodiment, the calculating unit 824 can calculate influence scores that reflect the numbers of destinations. Thus, in the fifth embodiment, the influence score of each person can be calculated, with the number of destinations of transmission performed by the person being taken into account.
 In the first embodiment, the influence scores of the respective persons are calculated, with the types of destinations of transmission not being taken into account. Normally, types of destinations of e-mail transmission include "TO", "CC", and "BCC". An e-mail transmission destination under "TO" is a "main transmission destination", and an e-mail transmission destination under "CC" or "BCC" is a "sub transmission destination". Where e-mail having its destination under "TO" is compared with e-mail having its destination under "CC" or "BCC", the relationship between the transmitter of the e-mail having its destination under "TO" and the receiver of the e-mail is stronger than that between the transmitter of the e-mail having its destination under "CC" or "BCC" and the receiver of the e-mail. In view of this, influence scores are calculated in this embodiment, with the types of transmission destinations being taken into account.
 In this embodiment, the mail information acquired by the relationship list generating unit 812 in the predetermined period T is the mail information shown in FIG. 20. In accordance with the relationship list supplied from the relationship list generating unit 812, the adjacency matrix generating unit 814 generates an adjacency matrix. The relationship list of this embodiment is shown in FIG. 21. In a case where there is e-mail transmitted to two or more destinations, the adjacency matrix generating unit 814 extracts the types of the destinations of the e-mail. In the example shown in FIG. 20, the person A has transmitted e-mail to the person B as a destination under "TO", and transmitted the e-mail to the person C as a destination under "CC". In this case, the adjacency matrix generating unit 814 multiplies the element indicating that e-mail has been transmitted from the person A to the person B (the main transmission destination) by a coefficient .alpha..sup.TO. The adjacency matrix generating unit 814 also multiplies the element indicating that e-mail has been transmitted from the person A to the person C (the sub transmission destination) by a coefficient .alpha..sup.CC. Here, .alpha..sup.TO>.alpha..sup.CC. For example, .alpha..sup.TO may be "1", while .alpha..sup.CC is "0.8". In this example, .alpha..sup.TO is "1", and .alpha..sup.CC is "0".
 Consequently, the adjacency matrix generating unit 814 generates an adjacency matrix by extracting only the e-mail transmission destinations under "TO".
 FIG. 24 shows an adjacency matrix Z3 to be used in the sixth embodiment in the form of a table. The calculating unit 824 calculates influence scores in accordance with the adjacency matrix Z3. For example, the calculating unit 824 calculates influence scores, using an equation formed by substituting Z.sub.kn in Equation 1 with Z3.sub.kn. In the sixth embodiment, the first communication history includes the type of a second person as a destination to which the first person has transmitted e-mail. The second communication history includes the type of a third person as a destination to which a second person has transmitted e-mail. Alternatively, the first communication history and the second communication history may include the type of a second person as a destination from the first person, and the type of a third person as a destination from a second person.
 According to the sixth embodiment, the calculating unit 824 can calculate influence scores that reflect the types of destinations. Thus, in the sixth embodiment, the influence score of each person can be calculated, with the types of destinations of transmission performed by the person being taken into account.
 In the fourth embodiment described above, the calculating unit 824 calculates influence scores, using the adjacency matrix Z1 that reflects the number of times communication has been performed. In a seventh embodiment, the calculating unit 824 calculates influence scores, using an adjacency matrix Z4 that reflects the number of times transmission has been performed but does not reflect the number of times reception has been performed in the number of times communication has been performed. For example, if information to spread across the network is transmitted to a person who has performed transmission a large number of times (or a person who frequently transmits e-mail), the information can appropriately spread across the entire network. In other words, the number of times transmission has been performed can be regarded as an index of easiness of information transmission in the network. In view of this, influence scores are calculated in this embodiment, with the number of times transmission has been performed being taken into account.
 In this embodiment, the mail information acquired by the relationship list generating unit 812 in the predetermined period T is the mail information shown in FIG. 20. In accordance with the relationship list supplied from the relationship list generating unit 812, the adjacency matrix generating unit 814 generates an adjacency matrix. The relationship list of this embodiment is shown in FIG. 21. The adjacency matrix generating unit 814 also extracts the number of times transmission from the first person to other persons has been performed. In the example shown in FIG. 20, the person A has transmitted e-mail to the person B, the person C, and the person D once each.
 FIG. 25 shows the adjacency matrix Z4 to be used in the seventh embodiment in the form of a table. The calculating unit 824 calculates influence scores in accordance with the adjacency matrix Z4. For example, the calculating unit 824 calculates influence scores, using an equation formed by substituting Z.sub.kn in Equation 1 with Z4.sub.kn. In the seventh embodiment, the first communication history includes the number of times transmission from the first person to a second person has been performed. The second communication history includes the number of times transmission from the second person to a third person has been performed. Alternatively, the first communication history and the second communication history may include the number of times transmission from the first person to a second person has been performed, and the number of times transmission from the second person to a third person has been performed.
 According to the seventh embodiment, the calculating unit 824 can calculate influence scores that reflect the numbers of times transmission has been performed. Thus, in the seventh embodiment, the calculating unit 824 can calculate influence scores that reflect easiness of information transmission in the network.
 In the seventh embodiment described above, the calculating unit 824 calculates influence scores, using an adjacency matrix Z4 that reflects the number of times transmission has been performed but does not reflect the number of times reception has been performed in the number of times communication has been performed. In an eighth embodiment, on the other hand, the calculating unit 824 calculates influence scores, using an adjacency matrix Z5 that reflects the number of times reception has been performed but does not reflect the number of times transmission has been performed in the number of times communication has been performed. For example, a person who has received e-mail a large number of times (a person who frequently receives e-mail) is a person who has various kinds of information. In view of this, influence scores are calculated in this embodiment, with the number of times e-mail has been received being taken into account.
 In this embodiment, the mail information acquired by the relationship list generating unit 812 in the predetermined period T is the mail information shown in FIG. 20. In accordance with the relationship list supplied from the relationship list generating unit 812, the adjacency matrix generating unit 814 generates an adjacency matrix. The relationship list of this embodiment is shown in FIG. 21. The adjacency matrix generating unit 814 also extracts the number of times the first person has received e-mail from another person. In the example shown in FIG. 20, the person A has received e-mail from the person B and the person D once each.
 Meanwhile, the adjacency matrix Z5 (now shown) is a transposed matrix Z4.sup.T of the adjacency matrix Z4. The adjacency matrix generating unit 814 may generate the adjacency matrix Z5, in accordance with the relationship list supplied from the relationship list generating unit 812. The adjacency matrix generating unit 814 also generates the adjacency matrix Z4, and further generates the transposed matrix Z4.sup.T of the adjacency matrix Z4 as the adjacency matrix Z5.
 According to the eighth embodiment, the calculating unit 824 can calculate influence scores that reflect the numbers of times reception has been performed. Thus, in the eighth embodiment, the calculating unit 824 can calculate influence scores that reflect how wide the variety of information (as to the conditions of the entire network and the like) held by each person.
 Next, influence score display by the display device 10 in a case where at least one of the fourth through eighth embodiments is applied is described. First, the influence score DB in a case where at least one of the fourth through eighth embodiments is applied is described. FIG. 26 is a diagram showing an example of the influence score DB in a case where at least one of the fourth through eighth embodiments is applied.
 The influence score DB shown in FIG. 26 stores not only the influence score DB shown in FIG. 12 (the influence score DB that takes nothing into account as shown in FIG. 26), but also an influence score DB that takes the types of destinations into account, and an influence score DB that takes into account the number of times reception has been performed. The influence score DB that takes account the types of destinations is an influence score DB that stores the influence scores of the respective persons calculated in the sixth embodiment. The influence score DB that takes account the number of times reception has been performed is an influence score DB that stores the influence scores of the respective persons calculated in the eighth embodiment. It should be noted that the respective influence scores shown in FIG. 26 are not communication histories of the respective persons A through D shown in FIG. 20, but are calculated with respect to other communication histories (not shown) of the respective persons A through D.
 Other names are also given to influence scores in accordance with the items taken into account. FIG. 27 is a table showing the correspondence between influence scores and other names given to the influence scores. The other names are stored in the DB 6. In the example shown in FIG. 27, another name for "influence score with nothing taken into account" is defined as "regular influence score". Another name for "influence score with destination types taken into account" is defined as "determiner score". Further, another name for "influence score with number of times reception has been performed taken into account" is defined as "consulting score".
 FIG. 28 is a diagram showing an example of the input screen to be displayed by the display 105 in a case where at least one of the fourth through eighth embodiments is applied. The input screen shown in FIG. 28 is the same as the input screen shown in FIG. 15, except that a search standpoint input region 210 to which the user can also input a search standpoint is also provided. The search standpoint input region 210 is a region to which the user can input a search standpoint. A search standpoint is a standpoint of an influence score to be displayed. The search standpoints of this embodiment correspond to the other names for the influence scores shown in FIG. 27.
 For example, when the cursor is moved onto the search standpoint input region 210, a tab showing all the search standpoints (or the other names shown in FIG. 27) is displayed. As the user selects a search standpoint from among the search standpoints displayed in the tab, the selected search standpoint is input to the search standpoint input region 210. When the search button 204 is clicked with the domain name having been input to the input region 202 and the search standpoint having been input to the search standpoint input region 210, the influence score display screen shown in FIG. 29 is displayed.
 FIG. 29 shows an example case where "qqq.com" is input as the domain name, and "determiner score" is input as the search standpoint. In the example shown in FIG. 29, "persons with high determiner scores at qqq.com" are displayed. In the example shown in FIG. 29, the person E, the person C, and the person D have higher determiner scores in this order in the group Q.
 As described above, with influence score display in a case where at least one of the fourth through eighth embodiments is applied, it is possible to display influence scores at search standpoints input by users. Thus, the user can be made to recognize more minute influence scores.
 The present invention is not limited to the above embodiments, and various other changes and modifications can be made. In the description below, modifications that can be applied to the present invention are described.
 In the first embodiment, D.sub.i(X.sub.i) represents the total number of persons of the first through jth generations counted from the person X.sub.i. Alternatively, D.sub.j(X.sub.i) may represent the number of persons of the jth generation counted from the person X.sub.i, and does not include the number of persons of the first through (j-1)th generations.
 In the case of such a configuration, Equation 3 for calculating the influence score of the person B turns into Equation 3' shown below.
 Alternatively, D.sub.j(X.sub.i) may represent the number of persons of the jth generation counted from the person X.sub.i, and not include the number of persons of the first through (j-1)th generations. With such a configuration, the amount of calculation can be made smaller than that in the case with Equation 3.
 Of the embodiments described above, at least two embodiments may be used. For example, the influence score C(X.sub.i) of the first person calculated according to Equation 1 or Equation 2 described in the first embodiment may be made to reflect the influence score C1(X.sub.i) of the first person calculated according to Equation 21 described in the second embodiment. Here, the calculating unit 824 may calculate the influence score of the first person, using one of the reflection formulas described below as a method of causing the reflection. According to a reflection formula, C(X.sub.i) may be multiplied by C1(X.sub.i). According to another reflection formula, C1(X.sub.i) may be added to C(X.sub.i). Further, any reflection formula may be employed, as long as the reflection formula can cause C(X.sub.i) to reflect C1(X.sub.i).
 For example, the influence score C(X.sub.i) of the first person calculated according to Equation 1 or Equation 2 described in the first embodiment may be made to reflect the betweenness centrality B(X.sub.i) of each person described in the third embodiment. Here, the calculating unit 824 may calculate the influence score of the first person, using one of the reflection formulas described below as a method of causing the reflection. According to a reflection formula, C(X.sub.i) may be multiplied by B(X.sub.i). According to another reflection formula, B(X.sub.i) may be added to C(X.sub.i). Further, any reflection formula may be employed, as long as the reflection formula can cause C(X.sub.i) to reflect B(X.sub.i).
 In the above described embodiments, an influence score is "the influence score of the subject person on the other persons (five persons) among all the persons specified in the relationship list. However, an influence score may not necessarily be such a concept, and may be some other concept. For example, an influence score may be any concept, as long as it is the influence score of the first person on multiple persons including the second person and the third person. The multiple persons may include the first person. Alternatively, the group to which the first through third persons belong may include a person with which any of the first through third persons has not communicated in the predetermined period T.
 (1) In the above described embodiments, the information to be used for calculating an influence score is the first communication history and the second communication history. However, the calculating unit 824 may calculate an influence score, using information related to neither the first communication history nor the second communication history. That is, the calculating unit 824 may calculate an influence score in accordance with calculation information including the first communication history and the second communication history.
 In the above described second embodiment, eigenvector centricity can be regarded as a concept included neither in the first communication history not in the second communication history. In the present invention, eigenvector centricity is a concept included neither in the first communication history nor in the second communication history, but is included in the calculation information. Therefore, even though eigenvector centricity is a concept included neither in the first communication history nor in the second communication history, the calculating unit 824 calculates an influence score in accordance with the calculation information including the eigenvector centricity. Also, even if at least one of the concepts (the number of times communication has been performed, for example) described in the third through eighth embodiments is a concept included in neither the first communication history nor the second communication history, the calculating unit 824 calculates an influence score in accordance with the at least one of the concepts. Further, the calculation information including the first communication history and the second communication history may be "a communication history including the first communication history and the second communication history".
 (2) The first acquiring unit 818 may acquire the first communication history of the subject person (the first person) with respect to each of the other persons specified in the relationship list. The second acquiring unit 820 may acquire the second communication history of a person who communicates with the subject person (the first person), with respect to each of the other persons specified in the relationship list.
 (3) In the above described embodiments, the calculating unit 824 calculates an influence score that reflects the persons up to the second generation counted from the first person. However, the calculating unit 824 may calculate an influence score that reflects the persons up to the Lth (L being an integer of 3 or greater) generation, using Equation 1. With such a configuration, it is possible to calculate a more accurate influence score.
 (4) In the first embodiment, when an influence score is calculated, the calculation result is multiplied by the coefficient a corresponding to the generation, as shown in Equation 1 or Equation 2. However, the multiplication using the coefficient a may not be performed. With such a configuration, the process of multiplication using the coefficient a is skipped, and the number of processes can be reduced accordingly.
 In the above described embodiments, the influence scores of all the persons specified in the relationship list are calculated. However, instead of the influence scores of all the persons, the influence score of a predetermined person of all the persons may be calculated. The predetermined person may be designated by a user, for example. In such a configuration, only the influence score of the person whose influence score the user wishes to know is calculated. Accordingly, the amount of processing in influence score calculation is smaller than that in an influence calculation device that calculates the influence scores of all the persons.
 The essential aspect of the present invention can be regarded as software stored in a flash memory or some other recording medium, or software that can be downloaded via a network. The recording medium may not necessarily be a DVD-ROM, a CD-ROM, an FD, or a hard disk, but may be a medium that carries a program in a static manner, such as a magnetic tape, a cassette tape, an optical disk, an optical card, a mask ROM, an EPROM, an EEPROM, or a semiconductor memory like a flash ROM. Alternatively, the recording medium is a non-transitory medium from which the program and the like can be read by a computer. Meanwhile, the program herein may not be a program that can be directly executed by the CPU, but may be a program in a source program format, a compressed program, an encrypted program, or the like.
 Although embodiments of the present invention have been described and illustrated in detail, it is clearly understood that the same is by way of illustration and example only and not limitation, the scope of the present invention should be interpreted by terms of the appended claims. It should be understood that equivalents of the claimed inventions and all modifications thereof are incorporated herein. Further, the inventions described in the embodiments and the respective modifications are intended to be carried out independently of one another or in combination, wherever possible.


This diving duck, restricted to North America, breeds widely throughout the Prairie Pothole Region of the United States and Canada. It also nests in dense concentrations in marshes of the western United States. In contrast to its extensive breeding distribution, the Redhead in winter is concentrated mostly in coastal areas along the Gulf of Mexico, with hundreds of thousands of birds traditionally found in the Laguna Madre of Texas and the Laguna Madre of Tamaulipas, Mexico.
The Redhead begins arriving in its winter range in October. The species depends heavily on rhizomes of shoalgrass (Halodule wrightii), a seagrass species, for winter nutrition. Pairs begin to form on the winter range, and by the time the last birds have left on their northward migration in March, pair formation is well under way. Monogamous pair bonds continue developing rapidly in small migrating flocks, with birds initiating nesting by early May and extending at least into late June. Nests are constructed in dense emergent vegetation (usually cattail [Typha] or bulrush [Scirpus] spp.) of deep marshes.
The Redhead demonstrates facultative brood parasitism to a greater extent than any other North American duck. A breeding female chooses 1 of 3 laying strategies: (1) lays her own clutch, (2) parasitizes other nests before laying her clutch, or (3) parasitizes other duck nests without producing a clutch of her own. Inter- and intraspecific egg parasitism is very common with this species; parasitic egg-laying has been known to increase nest abandonment and depress clutch size, nest success, and egg success for some host species. Males usually abandon their mates early in incubation, after which they and unsuccessful females congregate in large flocks on Canadian lakes to undergo molt and to stage for fall migration.
This wide-ranging species exhibits a high degree of flexibility in habitat and food use and reproductive behavior, yet, paradoxically, its numbers consistently are surpassed by populations of most other prairie-nesting ducks of North America. Many aspects of Redhead biology are well known: e.g., timing and routes of continental migration, courtship behavior, and pairing chronology (Weller Weller, M. W. (1964a). Distribution and migration of the Redhead. J. Wildl. Manage. 28:64-103.
Weller 1964a, Weller, M. W. (1965b). Chronology of pair formation in some of the Nearctic Aythya (Anatidae). Auk 82:227-235.
Weller 1965b, Weller, M. W. (1967a). Courtship of the Redhead (Aythya americana). Auk 84:544-559.
Weller 1967a; Johnsgard, P. A. (1965). Handbook of waterfowl behavior. Ithaca, NY: Cornell Univ. Press.
Johnsgard 1965; Bergman, R. D. (1973). Use of southern boreal lakes by postbreeding Canvasbacks and Redheads. J. Wildl. Manage. 37:160-170.
Bergman 1973); nesting ecology, reproductive biology, breeding habitat, and brood parasitism in Utah, Iowa, Manitoba, Montana, and North Dakota ( Williams, C. S. and W. H. Marshall. (1938). Duck nesting studies, Bear River Migratory Bird Refuge, Utah, 1937. J. Wildl. Manage. 2:29-48.
Williams and Marshall 1938; Low, J. B. (1945). Ecology and management of the Redhead, Nyroca americana, in Iowa. Ecol. Monogr. 15:35-69.
Low 1945; Weller, M. W. (1959b). Parasitic egg laying in Redhead (Aythya americana) and other North American Anatidae. Ecol. Monogr. 29:333-365.
Weller 1959b; Lokemoen Lokemoen, J. T. (1966). Breeding ecology of the Redhead duck in western Montana. J. Wildl. Manage. 30:668-681.
Lokemoen 1966, Lokemoen, J. T. (1991). Brood parasitism among waterfowl nesting on islands and peninsulas in North Dakota. Condor 93:340-345.
Lokemoen 1991; Kantrud, H. A. and R. E. Stewart. (1977). Use of natural basin wetlands by breeding waterfowl in North Dakota. J. Wildl. Manage. 41:243-253.
Kantrud and Stewart 1977; Sorenson, M. D. (1991). The functional significance of parasitic egg laying and typical nesting in Redhead ducks: an analysis of individual behaviour. Anim. Behav. 42:771-796.
Sorenson 1991; Sayler, R. D. (1996). Behavioral interactions among brood parasites with precocial young: Canvasbacks and Redheads on the Delta Marsh. Condor 98:801-809.
Sayler 1996). Recent advances have been made in estimating survival of Redhead ducklings and females ( Yerkes, T. (2000a). Influence of female age and body mass on brood and duckling survival, number of surviving ducklings, and brood movements in Redheads. Condor 102:926-929.
Yerkes 2000a, Arnold, T. W., M. G. Anderson, M. D. Sorenson and R. B. Emery. (2002). Survival and philopatry of female Redheads breeding in southwestern Manitoba. J. Wildl. Manage. 66:162-169.
Arnold et al. 2002); time-activity budgets in winter in Texas, Louisiana, and Tamaulipas ( Mitchell, C. A., T. W. Custer and P. J. Zwank. (1992). Redhead duck behavior on lLower Laguna Madre and adjacent ponds of southern Texas. Southwest. Nat. 37:65-72.
Mitchell et al. 1992, Michot, T. C., E. B. Moser and W. Norling. (1994b). Effects of weather and tides on feeding and flock positions of wintering Redheads in the Chandeleur Sound, Louisiana. Hydrobiologia 279/280:263-278.
Michot et al. 1994b, Woodin, M. C. (1994). Use of saltwater and freshwater habitats by wintering Redheads in southern Texas. Hydrobiologia 279/280:279-287.
Woodin 1994, Adair, S. E., J. L. Moore and Jr. Kiel, W. H. (1996). Wintering diving duck use of coastal ponds: an analysis of alternative hypotheses. J. Wildl. Manage. 60:83-93.
Adair et al. 1996, Vázquez, M. A., H. Suzán and M. Woodin. (1996). Comportamiento invernal del pato cabeza roja (Aythya americana) en la Laguna Madre de Tamaulipas, Mexico. Biotam 7:25-30.
Vázquez et al. 1996); foods and foraging ecology of breeders ( Bartonek, J. C. and J. J. Hickey. (1969a). Food habits of Canvasbacks, Redheads, and Lesser Scaup in Manitoba. Condor 71:280-290.
Bartonek and Hickey 1969a, Noyes, J. H. and R. L. Jarvis. (1985). Diet and nutrition of breeding female Redhead and Canvasback ducks in Nevada. J. Wildl. Manage. 49:203-211.
Noyes and Jarvis 1985, Jarvis, R. L. and J. H. Noyes. (1986). Foods of Canvasbacks and Redheads in Nevada: paired males and ducklings. J. Wildl. Manage. 50:199-203.
Jarvis and Noyes 1986, Woodin, M. C. and G. A. Swanson. (1989). Foods and dietary strategies of prairie-nesting Ruddy Ducks and Redheads. Condor 91:280-287.
Woodin and Swanson 1989, Kenow, K. P. and D. H. Rusch. (1996). Food habits of Redheads at the Horicon Marsh, Wisconsin. J. Field Ornithol. 67:649-659.
Kenow and Rusch 1996), of postbreeding birds on Manitoba lakes ( Bailey, R. O. and R. D. Titman. (1984). Habitat use and feeding ecology of postbreeding Redheads. J. Wildl. Manage. 48:1144-1155.
Bailey and Titman 1984), and of wintering birds in Texas and Louisiana ( Mcmahan, C. A. (1970). Food habits of ducks wintering on Laguna Madre, Texas. J. Wildl. Manage. 34:946-949.
Mcmahan 1970, Cornelius, S. E. (1977). Food and resource utilization by wintering Redheads on lower Laguna Madre. J. Wildl. Manage. 41:374-385.
Cornelius 1977, Michot, T. C. and A. J. Nault. (1993). Diet differences in Redheads from nearshore and offshore zones in Louisiana. J. Wildl. Manage. 57:238-244.
Michot and Nault 1993, Mitchell, C. A., T. W. Custer and P. J. Zwank. (1994). Herbivory on shoalgrass by wintering Redheads in Texas. J. Wildl. Manage. 58:131-141.
Mitchell et al. 1994, Woodin, M. C. (1996). Wintering ecology of Redheads (Aythya americana) in the western Gulf of Mexico region. Gibier Faune Sauvage Game Wildl. 13:653-665.


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Believing: Our Thirty-Year Journey to End Gender Violence (Large Print / Paperback)
By Anita Hill
Anita Hill is University Professor of Social Policy, Law, and Women's and Gender Studies at Brandeis University. After the 1991 Senate confirmation hearings for U.S. Supreme Court nominee Clarence Thomas, Hill became a leading figure in the fight for women's rights and against gender-based violence. She has written for The New York Times and Newsweek, and is a sought-after speaker.
Publication Date: November 9th, 2021
Social Science / Sexual Abuse & Harassment
Law / Gender & the Law

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Herman Cain was "somber" when he told a staffers that he would "reassess" whether the latest allegation of sexual impropriety made it impossible to continue his campaign, but by Tuesday night Cain had his game face back on.
Those few hours Tuesday might have been the only time Cain -- author of such works as The C.E.O. of Self and the somewhat premature This Is Herman Cain! My Journey to the White House -- has felt the sting of self-doubt in many years. T.A. Frank chronicled Cain's "healthy self-regard" for The New York Times Magazine earlier this month ("It takes self-regard to write of your only sibling, Thurman, who died at age 52 after years of substance abuse, and end it on this note: 'I loved my brother dearly and still grieve over his untimely death. And I know that he is looking down proudly on my incredible journey.'").
Cain's decision to review whether to campaign in early states or to hit general election swing states too, as he told the Collegian, comes as Politico's Jonathan Martin nominates Cain's campaign for the "most hapless and bumbling" in modern history. Take just one example: New Hampshire consultant Mike Dennehy told Martin that Cain's decision to give a disastrous interview to the Milwaukee Journal-Sentinel and snub the New Hampshire Union-Leader was "a colossal mistake that makes one think that they are smoking something illegal as they make decisions." But Martin notes the decision likely had nothing to do with narcotics and everything to do with football. Cain told the Journal-Sentinel, "My chief of staff and my assistant, they wanted to go to a football game, and I said yes!" In fairness, Cain did shake hands with his fellow Green Bay Packers tailgaters. This is the first time Cain has shown any signs that he might rethink his campaign strategy. As he struggled to deal with allegations that sexually harassed some women in the 1990s, Cain issued a defiant statement on November 7 saying he wouldn't play by "the media's rules." Cain explained, "Another reason I refuse to play by these rules is that, by doing it my way, I'm getting much better results. My fundraising has skyrocketed since all this nonsense began. Just this weekend, the Washington Post has come out with a new poll – taken since all this started – showing me in the lead nationally, with my numbers on the rise."
Cain emailed supporters asking for donations in this difficult time Tuesday night, explaining that he "helped [Ginger White] financially at times over the past few years" just as he has other, totally platonic, friends. And now he's the victim, he says, as "Ms. White has made it apparent that she was abusing the friendship." But one of the things that made White believable was the way her description of his personality rang so true: "Very arrogant in a playful sometimes way. Very, ah -- Herman Cain loves Herman Cain."


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Nomadic: people who move around all the time looking for food.
Bering Strait: body of water between lands ancestors of Native Americans crossed the land bridge to North America.
Middle ages: was a time of Black Death.
Crusades: series of wars undertaken by European Christians between the 11th and 14th cent. To recover the Holy Land from the Muslims.
Printing press: advance of European technology to print newspaper.
Brought the potato, the pineapple, the turkey, dahlias, sunflowers, magnolias, maize, chilies and chocolate across the Atlantic.
On the other hand, tens of millions died in the pandemics of the 16th century, victims of smallpox, measles and the other diseases brought by Europeans (and don't forget that the African slave trade was begun by the Europeans, to replace the work force they had decimated).
Conquistador: an adventurer military leader in the Spanish conquest of the New World in the 16th cent. Francisco Pizarro, the conqueror of Peru, and Hernán Cortés, the conqueror of Mexico, were the greatest of the conquistadors. The name is frequently used to mean any daring, ruthless adventurer.
WriteWork contributors. "Us 1 history midterm study guide...might as well help other people it is a guide to everything on my midterm review sheet" WriteWork.com. WriteWork.com, 15 February, 2005. Web. 18 Apr. 2019.
Not very detailed, but pretty good for a review.


These sentiments correspond beautifully with your watercolor projects! "Beauty is all around you" "You brighten my day" "Heartfelt Gratitude" "Friendship Blooms from the heart" "Happiness Grows" "Thinking of you" "To a Dear Friend" "Your kindness spreads like sunshine" "Love you a bunch!" Largest sentiment is 3.5″ long and smallest sentiment is 1.5″ long. This is a clear stamp set.


Easy 30-Minute Chicken Chimichanga Recipe – it is a baked burrito, stuffed with chicken, cheese and mild chilies.
They are crispy from the outside, cheesy & juicy on the inside.
Chimichangas are very popular in Mexico and in my kitchen.
I love preparing this Mexican food recipe way ahead before dinner. I cook chicken, shred cheese, chop salad, then fold each chimichangas and place them in the refrigerator. 15 minutes before dinner I brush them with butter and bake them until golden color.
They are super crispy, moist, and hubby-approved.
Try them for yourself, and let me know what you think!
Step 1. Bring large saucepan filled half way with water to a boil, add chicken breast and cook on medium/high heat until chicken is cooked thru and it is no longer pink inside, about 10 minutes. Drain the water and let it cool. Using hands or two forks tear the chicken into small pieces.
Step 2. In a mixing bowl combine chicken, ground cumin, cheese, chillies, Mexican White Sauce, salt and pepper. Give it a good mix. Warm tortillas on top of the stove for few seconds, it will make them soft and flexible.
Step 3. Place 1/2 cup of the chicken mixture on center of each tortilla.
…then the bottom side up to cover the filling… roll over to create chimichangas.
…roll over to create chimichanga.
Step 5. After you are done, place chimichangas on a baking dish.
Step 6. Brush each chimichanga with butter and bake for 12-15 minutes or until golden color.
Step 7. Serve with leftover Mexican White Sauce, Homemade Guacamole or cabbage salad.
Did you like this 30-Minute Chicken Chimichanga Recipe?
Delicious Chicken Chimichanga Recipe - it is a baked burrito, stuffed with chicken, cheese and mild chilies.
Bring large saucepan filled half way with water to a boil, add chicken breast and cook on medium heat until it is cooked thru and chicken is no longer pink inside. Drain the water and let it cool. Using hands or two forks tear the chicken into small pieces.
Warm tortillas on top of the stove for few seconds, it will make them soft and flexible.
In a mixing bowl combine chicken, ground cumin, cheese, chillies, Mexican White Sauce, salt and pepper. Give it a good mix.
Place ½ cup of the chicken mixture on center of each tortilla. Fold the sides, then the bottom side up, to cover the filling, roll over to create chimichangas.
Brush each chimichangas with butter and bake for 12-15 minutes or until golden color. Serve with leftover Mexican White Sauce, Guacamole or cabbage salad.
If you make Easy Chicken Chimichanga Recipe for lunch or dinner, please tag my name @munchkintimeblog and hashtag #munchkintimeblog on Instagram, I would LOVE to see your creation!
Don't miss another yummy recipe subscribe to Munchkintime on the bottom of this post.
Last time i made these, i made them without the mexican sauce in them cause either i didnt see it in the ingredient list or i made them when you hadn't added that in yet. So made without the sauce in them, they were good, just dry and I wondered why mine turned out so dry. But making these again and putting the sauce in this time, i tasted the sauce and its really good, i think these are going to be amazing when finished!
I made these! I cooked about six mins longer and they still were not browned. They did not turn out crunchy and were thought to cut for the kids. I would recommend putting something else in with just the three ingredients didn't have much taste..
Thank you, Amy for the recipe review! I appreciate you writing it. I took your review in consideration and made a delicious Mexican White Cream to add inside the Chicken Chimichangas to make them extra juicy on the inside. I hope you will give this recipe another try and let me know what you think. Happy Friday!
Made these tonight. They were delicious! I added green onions and my oven took a lot longer to brown. I will definitely make again!
I don't like diced mild chilles is there anything else I can substitute with?


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Phillip Gariseb (born 6 September 1973) is a Namibian footballer. He played in 18 matches for the Namibia national football team from 1995 to 1999. He was also named in Namibia's squad for the 1998 African Cup of Nations tournament.

References

External links

1973 births
Living people
Namibian men's footballers
Namibia international footballers
1998 African Cup of Nations players
Place of birth missing (living people)
Association footballers not categorized by position

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It may be necessary to ask your Trained Observer for assistance when putting on the outer gloves. Double gloving provides an extra layer of safety during direct patient care and during the PPE removal process. Some facilities have found that using a different color gloves for the outer gloves is beneficial. Utilizing different colored gloves for each layer helps to rapidly identify any breaches in glove integrity.


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Semtech and Helium expand LoRaWAN network deployments
in Networking
Semtech Corporation, a supplier of high performance analog and mixed-signal semiconductors and advanced algorithms, announced its expanded collaboration with Helium, the company behind one the world's first peer-to-peer wireless networks based on Semtech's LoRa devices and the LoRaWAN protocol.
Today, Helium's LoRaWAN network infrastructure is considered among the fastest growing of its kind, reaching more than 1,000 cities in North America and expanding to Europe. Earlier this year, Helium announced a strategic partnership with Semtech to integrate the LoRaWAN protocol into its LongFi networking architecture.
"Helium has seen incredible growth on its network as a result of its partnership with Semtech and the introduction of the Helium Blockchain as an incentive model to the LoRaWAN community," said Amir Haleem, Helium's CEO and Co-founder. "As we continue to expand the network across North America and in Europe, we hope to foster the growth of the ecosystem and make new technologies and solutions available to developers, industries and ultimately, consumers."
Helium's network is powered by the Helium Hotspot, a device enabling end consumers to own and operate a LoRa-based wireless network for the Internet of Things (IoT). When connected to a nearby Hotspot, devices simultaneously mine cryptocurrency and provide LoRaWAN network coverage for hundreds of square miles. Combining Semtech's LoRa devices with Helium's distributed, open-sourced approach to building a ubiquitous network allows the simplified deployment of applications across North America and Europe. In less than six months following Semtech and Helium's initial collaboration, more than 10,000 Helium Hotspots have been sold.
Featuring a community of more than 8,000 software developers in the LoRa ecosystem, the network is currently available to connect up to hundreds of millions of compatible LoRa-based devices.
As part of its mission to grow its LoRaWAN network offerings, Helium has entered a multi-year strategic alliance with Cal-Chip Connected Devices, a division of Cal-Chip Electronics Specialty Products, Inc., and a global distributor and value added service provider in the IoT space with a focus on Semtech's LoRa devices. As part of this agreement, the organisation plans to help distribute Helium-compatible LoRa-based solutions, including third-party gateways and sensors, for use throughout North America and Europe.
"Semtech delivers the technology, Helium delivers the network and Cal-Chip delivers the devices. Cal-Chip has the infrastructure and technical 'know-how' to present solutions in an easy-to-understand manner, leading to an exceptional customer experience," said TJ Rancour, President of Cal-Chip Connected Devices. "By leveraging our logistics, customer service and technical proficiencies, Cal-Chip Connected Devices is enabling efficient user-friendly distribution of Semtech and Helium devices to a mass consumer market."
"Semtech is committed to the development of smarter IoT strategies which remove the complexity in developing LoRa-based products," said Marc Pegulu, Vice President of IoT Product Marketing in Semtech's Wireless and Sensing Products Group. "Through further collaboration with Helium, Semtech delivers end users and developers greater access to open-sourced networks and LoRa-based infrastructure. As a result, Helium's unique business model enables ownership and operation of personal IoT networks, promoting the development of new and innovative LoRa-based applications which increase the global adoption of the LoRaWAN protocol and accelerate solution time to market."
Infovista unveils NLA Cloud Platform
Edge computing key for rapid adoption of Industry 4.0
Yorkshire Water accelerates data innovation
Macquarie Government partners with Fortem Australia
Second generation FlashArray//C makes all-flash more accessible and renders hybrid solutions obsolete
Two new data centres delivered - despite COVID-19 impact